Hi cudawarped hope all is well!
Nice work 
I haven’t tried the methods you described yet as I am currently working on a big AI project. However your results are good.
I removed the beagle and pug classes from the training data. Then when I classified them using the trained model, many of the beagle images are “wrongly” classified as basset hounds. Which from a quick inspection seems understandable, I struggle to tell the difference between the two classes.
The reason I am asking about the alternative methods is because intuitively I wouldn’t expect a CNN (or even an expert in pets) to be able to distinguish between an unseen class that so closely resembles a class that a model is trained to detect (or expert has observed through their lifetime), but I may be wrong?
I agree with both your points above, in lesson 1 Jeremy talks about the difficulty of telling two types of cat apart. I don’t think its currently possible to tell two breeds or certain items apart if human experts can’t. I would think there must be some discernible differences to achieve classification. My own experience is the same as yours. This post, I did yesterday Lesson 1 Assignment - confused about results - #2 by mrfabulous1 describes the difficulties, classes with similar images present.
I will try the techniques you mention when I next build a classifier.
Cheers mrfabulous1